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Linking Partial and General Equilibrium Models: A GTAP Application Using TASTE

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  • Narayanan, Badri
  • Thomas Hertel
  • Mark Horridge

Abstract

CGE models are utilized for the evaluation of trade policy reforms, yet they are typically highly aggregated, limiting their usefulness to trade negotiators interested in impacts at the tariff line. Partial Equilibrium (PE) models used for disaggregate analysis lack the benefits of an economy-wide analysis required to examine the overall impact of trade policy reforms. This suggests the need for a PE-GE, nested modeling framework to support trade policy analysis. In this paper, we develop a PE model that captures international trade, domestic consumption and output, using CET and CES structures, market clearing conditions and price linkages, nested within the standard GTAP Model. In addition, we extend the welfare decomposition of Huff and Hertel (2001) to this PE-GE model to contrast the sources of welfare gain among models. To illustrate the value-added of this model, we examine the impact of multi-lateral tariff liberalization on the Indian economy, with special focus on the auto sector, using PE, GE and PE-GE models. The PE model does not predict the change in overall size and price level for the industry well, while the GE model underestimates the aggregate welfare gain due to tariff averaging. It also fails to account for the change in industry composition resulting from trade reform. These findings are robust to wide variation in model parameters. We conclude that the linked model is superior to both the GE and PE counterparts.

Suggested Citation

  • Narayanan, Badri & Thomas Hertel & Mark Horridge, 2010. "Linking Partial and General Equilibrium Models: A GTAP Application Using TASTE," GTAP Technical Papers 3192, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University.
  • Handle: RePEc:gta:techpp:3192
    Note: GTAP Technical Paper No. 29
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    2. Aguiar, Angel & Chepeliev, Maksym & Golub, Alla & Hertel, Thomas & Soderbery, Anson & van der Mensbrugghe, Dominique, 2020. "The role of trade elasticities in shaping uncertainty in CGE policy outcomes," Conference papers 333206, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    3. Beyhan Bektasoglu & Tanja Engelbert & Martina Brockmeier, 2017. "The Effect of Aggregation Bias: An NTB-modelling Analysis of Turkey's Agro-food Trade with the EU," The World Economy, Wiley Blackwell, vol. 40(10), pages 2255-2276, October.
    4. Erwin Corong & Thomas Hertel & Robert McDougall & Marinos Tsigas & Dominique van der Mensbrugghe, 2017. "The Standard GTAP Model, version 7," Journal of Global Economic Analysis, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University, vol. 2(1), pages 1-119, June.
    5. Joseph Francois & Miriam Manchin & Hanna Norberg & Olga Pindyuk & Patrick Tomberger, 2013. "Reducing Transatlantic Barriers to Trade and Investment: An Economic Assessment," Economics working papers 2015-03, Department of Economics, Johannes Kepler University Linz, Austria.
    6. He, Xi & Yang, Anton & Balistreri, Edward J. & Zhang, Wendong, 2021. "Agricultural Trade Impacts of RCEP: an Integrated Partial Equilibrium and General Equilibrium Assessment," Conference papers 333312, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    7. Nilsson, Lars, 2019. "Reflections on the economic modelling of free trade agreements," DG TRADE Chief Economist Notes 2019-2, Directorate General for Trade, European Commission.
    8. Ahmad, Saad & Riker, David, 2020. "Versatility and Specificity of PE Models for Trade Policy Analysis," Conference papers 333160, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    9. Jafari, Yaghoob & Britz, Wolfgang, 2018. "Modelling heterogeneous firms and non-tariff measures in free trade agreements using Computable General Equilibrium," Economic Modelling, Elsevier, vol. 73(C), pages 279-294.
    10. Brockmeier, Martina & Bektasoglu, Beyhan, 2014. "Model structure or data aggregation level: Which leads to greater bias of results?," Economic Modelling, Elsevier, vol. 38(C), pages 238-245.

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